In this month’s research spotlight, we highlight recent research from COSMOS that focuses on online toxicity diffusion, ways to computationally model its spread, and mitigation methods. These studies were published and presented recently at the 2024 Complex Networks & Their Applications (CNA) conference, which took place from December 10 to 12, 2024, in Istanbul, Turkey. Specifically, the studies we spotlight here are titled,
“Combating Toxicity: A Systematic Approach to Model Quarantine Intervention for Varied Toxicity Levels,” and
“Modeling Toxicity Propagation on Reddit using Epidemiology.”
Each of these studies focused on how online toxicity propagates on social media platforms, as well as how it can be mitigated. The former studied the impact of quarantining users in the novel SEIQR model, while the latter studied exhaustively the accuracy of five separate toxicity models.
“Combating Toxicity: A Systematic Approach to Model Quarantine Intervention for Varied Toxicity Levels” applied the SEIQR epidemiological model to analyze toxicity spread on social media platforms. Researchers examined datasets from COVID-19 and social movement discussions on X (Twitter), categorizing toxic content into moderate and high intensity levels. By splitting datasets, they achieved lower error rates in modeling toxicity propagation. A sensitivity analysis revealed key parameters influencing toxicity spread, including positive factors like infection rate and recruitment rate, and a negative factor in user exit rate. The research recommends various strategies for managing online toxicity based on the model’s findings.
“Modeling Toxicity Propagation on Reddit using Epidemiology” examined how epidemiological models can be applied to measure toxicity propagation on Reddit. The researchers tested five established models (SIS, SIR, SIRS, SEIR, SEIRS) on two datasets from Reddit. Results showed these models can achieve less than 2% fitting error when tracking toxicity spread. More complex models like SEIRS and SIRS performed significantly better than simpler ones like SIS, though SIRS worked well for linear data patterns. This research demonstrates epidemiological modeling’s effectiveness on Reddit and could inform future toxicity prevention strategies.
In an era where digital platforms shape global conversations, the threat of online deviance has never been more pressing. From influence campaigns to AI-driven manipulation, the digital battleground is evolving at an unprecedented pace. How can we detect and combat these threats while preserving open discourse?
TheDeviant Dynamics in Digital Spaces 2025 workshop (Deviance 2025) is an opportunity to engage with leading experts tackling the most pressing challenges in online safety and security. Hosted at ASONAM 2025 in Niagara Falls, Canada, during August 25-28, 2025, the workshop will bring researchers, policymakers, and industry leaders together to explore emerging challenges and opportunities for studying digital deviance and share the latest research in detection and mitigation.
Attendees will gain insights into misinformation detection, algorithmic exploitation, and cross-platform coordination strategies. Deviance 2025 will feature AI experts and social scientists working at the forefront of cognitive security. Join to discover cutting-edge research on trolling strategies, cognitive manipulation, and extremist recruitment tactics, and contribute to discussions on policy implications and governance frameworks shaping the future of digital safety.
We invite original research papers addressing
Influence and manipulation tactics & detection,
AI-enabled threats & countermeasures,
Algorithmic manipulation & recommendation system exploitation, and
Adversarial Human-AI teaming, social bot analysis, trolling, and hate speech detection.
Privacy & security in social media platforms
The following are important dates:
Submission Deadline: May 18, 2025
Acceptance Notification: June 1, 2025
Camera-ready Deadline: July 28, 2025
Accepted papers will be published in the ASONAM 2025 Conference Proceedings by Springer.
Join us in shaping the fight against digital deception. Submit your research today!Questions? Read more about the workshop or contact Dr. Nitin Agarwal at nxagarwal@ualr.edu.
The 51st National Convention of the National Society of Black Engineers (NSBE) proved to be an outstanding gathering, uniting aspiring engineers, experienced professionals, and industry leaders. Hosted in Chicago, Illinois, from March 5 to 9, 2024, the event served as a hub for knowledge sharing, networking, and career development for the attending cosmographers.
With numerous leading companies present and actively seeking talent, attendees had access to a wealth of internship and full-time job opportunities. From established tech corporations to innovative startups, recruiters focused on identifying top candidates. Cosmographers not only secured interviews but also left the convention feeling empowered, recognizing that their skills and expertise were highly valued.
Among the attendees were cosmographers Abiodun Quadri, Christopher Falade, Emmanuel Addai, Oyindamola Koleoso, and Ridwan Amure. Ridwan contributed to the event by delivering a workshop presentation on AI titled “Building and Deploying Retrieval-Augmented Generation (RAG) Systems for Quality Business Impact.”
We take great pride in seeing cosmographers engage in conferences, as these experiences expand their knowledge and professional networks.
“At COSMOS, we are committed to fostering high-talent individuals and training future innovators in STEM disciplines. Events like the NSBE convention play a crucial role in advancing that vision,” said Dr. Agarwal.
In this edition of Cosmographer Corner, we highlight the work of former University of Arkansas at Little Rock graduate and cosmographer Dr. Kim Tran. We are extremely proud of Dr. Tran’s accomplishments!
Dr. Tran—who is now a senior manager at Murphy USA—started her graduate education at UA Little Rock in 2005, studying first for her MBA in Business Administration and going on to pursue a PhD in Computer and Information Science, which she received in 2018. We interviewed Dr. Tran on where her career is now and what her work at COSMOS entailed, with her responses below.
How did COSMOS fit into your university career? How did you come across COSMOS and what were you studying when you joined COSMOS?
As you go through your PhD training, you have somebody that is your advisor and mentor. The way that you and your advisor work together is very strategic; in my case, there were initiatives that I knew Dr. Agarwal was involved in. There is going to be some type of research topic that you’re going to focus on. So he and I spent quite a bit of time trying to find a topic that I felt was germane to an area and that I thought I could be impactful in the field. With any PhD, the sky’s the limit—which also means that finding scope can be tough. So we really spent time walking through the potential impact of what was being done—initially just figuring out what the landscape, if you will, was, and then ultimately narrowing down a topic that we thought could be meaningful and provide contribution to the field. In my particular case, I was interested in what had potential business implications. At the time that I joined COSMOS, the space in social networking was beginning to be a little bit more congested, and there was a lot of interest in that area. I was trying to find something novel that would contribute to the field.
In other words, my work with COSMOS and Dr. Agarwal started when I was trying to figure out who I wanted to work with and my research area of focus for my PhD. One aspect was trying to find an area that interested me. And then the other was to find a good kind of dynamic. I visited with several different faculty members to learn about what their interests were, to get a sense of overlap of interest. So that’s really how we started working—I don’t know if ‘organic’ is the right word, but almost: it was based on a series of discussions that we had. And, of course, I had had some courses with Dr. Agarwal, as well. Through that, we were able to learn about things that were of shared interest to him and to me from a research perspective, some of the collaborations that he was engaged in, and I was able to see the potential synergies of working with him and as a team.
How did COSMOS contribute to your career and program at UALR? What was Dr. Agarwal’s role in your journeys during and after?
Currently, I am now in the private sector. The focus is less about research, per se, but there’s research in keeping up with the latest advances. With my work with Dr. Agarwal, a lot of our time was spent honing the topic, the direction and, in some instances, the approach, such as instances where I thought the methodology might need some level of refinement. With regards to building out my dissertation committee, these are all different things that we worked through together. Because at the end of the day, what you want when you’re presenting to the dissertation committee is that there are no surprises. So really, just having him work alongside me as my guide and mentor, that was very instrumental. There was also a point where there were some really amazing opportunities that were provided by Dr. Agarwal when I was graduating. I had actually spent some time talking through the various options with Dr. Agarwal; he was very instrumental in that regard.
How would you describe the “research pipeline” that you worked on while at COSMOS? In other words, what was the specific area in which you researched?
It was mostly about the development of a methodology. As you know, in the social network space, as well as even just social media space, there was at the time a lot of unstructured data. The question I had was, is there a way that you could leverage any of that data—not just at large—but in a way that you could work with a more focused subset of data? Namely, could you leverage it to see if it could provide efficacy in, say, early stage screening for pharmaceuticals, like the phase one of pharmaceutical trials? Take, for example, that you have a population rate of data for, in this case, patients who had idiopathic pulmonary fibrosis—a very localized group who has a unique subset of symptoms as well as a disease. If you could take that, what was the quality of data needed for that particular subset? Was there any industrial application for that kind of data, if you were to apply it to a more industrial setting? So part of my research was building out that methodology and seeing if there were actually a potential use case for that data.
Since leaving COSMOS, what positions have you had? What is your current work? What positions did COSMOS and your classes at UALR best prepare you for?
I have worked in a variety of sectors—everything from big box retail, small box retail, and over to business development and even higher ed. There was one opportunity that just happened to open up, where I had had some really good conversations with the company, around the time I graduated. In this case, the company was Murphy USA, where I now work. I handle pricing for merchandise at the company. It’s a little different than pure research, but some of the applications and use cases are still very germane, including model development, efficacy, data quality, and things of that nature, which all play a significant role in many of the things that we do. What’s fascinating is, of all the different things that I’ve learned over my time in a variety of industries, all of those processes have been highly applicable in what I do in the current day, whether it’s working with teams or working with more technical aspects. For example, if we’re leveraging a model, we need to know: is that model actually good? Does that model have any efficacy? What are the parameters that we need to better tune that model? Those are all things that have actually continued to play a role in how I do business.
If you had to describe the most momentous event at COSMOS, what would it be?
I remember attending a conference that had been founded by some folks over at MIT, that had a curriculum and program design to fit within the industry. I was a co-chair at the time, and another was Bill Inman, who’s colloquially known as the father of data warehousing. He ended up being a keynote speaker at that particular conference. What I remember vividly was a simple message; his takeaway was this: when we created technology as a field, the whole purpose was to solve problems. If we get to a point where the technology doesn’t solve a problem or is too complex, we need to rethink how we’re doing business. I thought that was so simple but also quite profound. It’s so easy to think about the tech stack that you’re using or the number of people that you need to implement a particular technology. But if you can do something that is highly complex in a much more simple manner, then that is worth evaluating. Whether it comes down to algorithm design or leveraging some of the latest features that are available through AI—whatever the case is—at all points one should think: here is this technology I’m using, but is it the optimal way to do this? You can do something super complex, but you should always ask, practically, what is the actual application? Does it have some potential use? And if it’s inefficient, is it actually worth your time?
What advice would you have for current Cosmographers?
For those in the program, I would say first and foremost, learn the latest platforms and technologies that are available. I say this because everything’s kind of converged. For the first time in the history of machine learning—namely AI and algorithms—we actually have AI at a point where it is highly usable. Whether you’re researching or it’s a part of your research agenda or not, you need to learn it. You need to learn how to leverage it because it will be important for the future, due to the implications of the technology. That’s one. Then, two—as I alluded to earlier—but if you have the option, try to find something that is applicable and has a potential business or use case. Applicability is very important.
Then, I would say my last advice is that—whether you’re researching, working part time, and or doing other things—I would encourage everybody to connect, build bridges, and put yourself out there. If you are in any engineering or tech space, it’s all too easy to just be thinking inside your head. You’ve got these ideas, or you’re constantly running math in your mind all the time, and it can be a very introspective process. But if you think of researchers as people, what do people do? People are there to connect with other people so that we’re part of a larger community. So it’s important to really get out there, and that’ll benefit you on a couple of fronts. If you’re a researcher, being able to connect with researchers in another state or multiple states, your research interests may converge. Or if you’re planning to possibly one day enter the private sector, you still never know when an opportunity may arise. Some of the best job opportunities I had happened because I was in the right place at the right time.
Springer’s Social Network Analysis and Mining (SNAM), a prestigious journal, publishes groundbreaking research at the intersection of computational and information sciences discipline and the social science discipline. Recently, SNAM published one of our studies titled, “KG-CFSA: A Comprehensive Approach for Analyzing Multi-source Heterogeneous Social Network Knowledge Graph,” the authors develop methods to fuse multisource heterogeneous data through knowledge graphs and contextual focal structure analysis for improving the state of the AI models that feed on such open datasets. Their paper names this method as KG-CFSA.
Specifically, the authors integrate data from multiple social networks, knowledge graph fusion, and contextual focal structure analysis to model relations across documents, entities, and topics. The method applies Cartesian merge techniques and enhances information with third-party data from WikiData and DiffBot. When applied to an Indo-Pacific region dataset, the system identified 40,000 unique focal sets discussing economics, elections, and policies. The approach effectively tracks information spread across multiple social media platforms and enhances visibility of vital information through various relationships, demonstrating KG-CFSA’s effectiveness in contextualizing large-scale multi-source information. For the Indo-Pacific dataset, KG-CFSA successfully extracted meaningful focal structures related to economic, political, and governmental discussions involving Indonesia and China.
Prof. Agarwal said, “This approach effectively contextualizes large-scale information flow and identifies focal structures that shape online discourse about significant regional matters, such as the Indo-Pacific Economic Framework and Belt and Road Initiative conversations. Moreover, this study develops ways to help improve AI model training by fusing multisource and heterogeneous open data across different platforms contextualized through knowledge graphs.” Click hereto read the full article.
The journal SNAM focuses on the theoretical and practical aspects of social network analysis and data mining. It covers interdisciplinary research in fields such as computer science, sociology, physics, economics, and more. Some key themes and ideas covered in SNAM are
Social network structures and dynamics,
Data mining and machine learning for networks,
Computational and algorithmic approaches,
Influence, diffusion, and community detection, and
Applications in social media, marketing, and behavioral analysis
The International Conference on Human and Social Analytics (HUSO) is an annual event dedicated to advancing research at the intersection of human behavior, social dynamics, and computational analytics. Bringing together scholars and professionals from diverse disciplines, the conference serves as a platform for discussing innovations in sentiment analysis, human-computer interaction, social computing, and digital heritage analytics. From March 9 to 13, 2025, the 11th HUSO conference was held at Lisbon, Portugal.
This year COSMOS presented the paper “Resilience and Node Impact Assessment in YouTube Commenter Networks Leveraging Focal Structure Analysis” at the conference, which won the conference’s Best Paper award. Their paper examined network resilience in YouTube networks using Focal Structure Analysis (FSA). The study identified key structures in commenters and video recommendation networks that lead to the emergence of content traps feeding into the AI and algorithmic bias. Researchers evaluated their study across 35 YouTube channels discussing Indo-Pacific topics. By analyzing 308,890 videos with over 1.5 million comments, they identified several focal structures, whose removal could significantly mitigate the effects of AI bias and influence tactics. FSA identified more impactful structures than state of the art methods.
As part of the talk series on Conversation with the Titans of Industry, world-renowned Arkansas executive Bobby Martin and Annemarie Dillard Jazic visited UA Little Rock’s campus to discuss their experiences in technology in business. The event was hosted at UA Little Rock’s Engineering and Information Technology (EIT) building on February 27th, with guests and invited speakers touring the facilities afterward. The Titans of Industry series focuses on hosting influential business leaders to give students and faculty practical business knowledge.
Bobby Martin is a distinguished business executive known for his leadership in retail technology and corporate governance. His career began at Dillard’s in 1969, and in 1984, he transitioned to Walmart, where he played a pivotal role in advancing retail technology. Most notably, Martin made history as the first Chief Information Officer (CIO) at Walmart to later move into a senior operational role, becoming the CEO of Walmart International. During his tenure, he spearheaded the company’s international expansion, increasing revenue to $30 billion over seven years.
Martin was joined by colleague Annemarie Dillard Jazic, the vice president of e-commerce and digital marketing and of information technology at Dillard’s. At Dillard’s, she oversees the company’s online retail strategy, digital marketing initiatives, and customer engagement efforts. Dillard Jazic joined Martin in discussing business practices that enhance the customer’s shopping experience.
Martin and Dillard Jazic both toured COSMOS facilities, where Prof. Agarwal explained the commercial applications of COSMOS’ research in AI, machine learning, data mining, and general data science, all funded by various grants from the U.S. Department of Defense and National Science Foundation. They discussed how COSMOS is creating tools with commercial and military uses for a wide range of tasks relating to digital campaigns and AI.
Catch a glimpse of the discussion at our YouTube channel here.
In this month’s research spotlight, we highlight recent research from COSMOS that focuses on information campaigns and socio-political protests. These studies were published and presented recently at the 2025 Hawaii International Conference on System Sciences (HICSS 2025), which took place from January 7 to 10, 2025, in Hilton Waikoloa Village, Big Island, Hawaii. Specifically, the studies we spotlight here are titled,
“Analyzing TikTok’s Role in Mobilizing Dynamics for Information Campaigns during Taiwan’s 2024 Elections,” and
“The Amplifiers of Dissent: Examining Influence of Key Users and Content Modality on Collective Actions.”
“Analyzing TikTok’s Role in Mobilizing Dynamics for Information Campaigns during Taiwan’s 2024 Elections” discovered how disinformation and anti-disinformation campaigns played out on TikTok during Taiwan’s 2024 presidential election. The study examined TikTok videos, their comments, and network relationships between commenters. Key findings showed that while disinformation campaigns relied on rapid, high-volume content bursts, anti-disinformation efforts succeeded through sustained, credible engagement that built trust over time. The anti-disinformation campaign generated significantly higher user engagement and maintained stronger network cohesion. The research suggested that successful online mobilization depends more on audience engagement during the amplification stage than on initial rapid content deployment.
“The Amplifiers of Dissent: Examining Influence of Key Users and Content Modality on Collective Actions,” examined the role of key social media users and content types (text and images) during the 2022 Brazilian anti-government protests on Instagram. The researchers analyzed how different types of influential users—identified through network centrality, engagement levels, and posting frequency—shaped emotional responses and mobilized protesters. Further, the study analyzed the role of influential users in collective identity formation in terms of evoking mobilization through different content modalities. The findings showed that text and images contribute differently to collective identity formation and mobilization.
This edition of the newsletter shares the academic journey of one of our recent graduates, Imran Mohammed, and what the future holds for him. Imran graduated with a master’s in computer science and worked as a graduate research assistant at the COSMOS Research Center.
“I am extremely proud of the accomplishments and the numerous contributions Imran has made to the COSMOS Research Center. We all celebrate his academic journey and wish him the best in his future pursuits,” said Prof. Agarwal.
Imran Mohammed
Tell us a little bit about yourself
I am Imran from India, and I have currently finished my Master’s in Computer Science at UA Little Rock. I love traveling.
What was your inspiration for joining COSMOS?
When I was looking for research opportunities at UA Little Rock, I discovered COSMOS. Their work caught my attention because it was both exciting and impactful. Prof. Agarwal and his team’s impressive achievements in the Social Computing field inspired me to apply for a position at COSMOS; I wanted to be part of such a talented team.
How has COSMOS helped in your journey?
I was part of a data object team at COSMOS. The data object team’s work was more emphasized on implementation and to build applications that all our Cosmographers could use to perform their research in natural language processing (NLP) and Social Computing tasks. As an implementation team, we got a chance to work in trending technologies, tools, and microservices at COSMOS, which gave me a lot of expertise and hands-on experience in emerging applications. Due to all the learning and research work at COSMOS, I was able to gain more exposure to work on emerging tech stack that directly helped me in gaining an internship position with the State of Arkansas.
What are your plans after graduation?
After completing my internship with the State of Arkansas Department of Commerce, I was offered a full-time position there. I plan to continue working with the State as I grow further in my career.
What is your fondest memory as a Cosmographer?
I really enjoyed our monthly outdoor COSMOS student appreciation and team building events hosted by Prof. Agarwal, where the whole team participated. It was great to spend quality time with everyone, getting to know each other better, enjoying food, and just having fun together.
Do you have any parting words for Cosmographers?
You are all doing amazing work. Keep it up! Your research is truly inspiring, and I hope you achieve all your goals. It was a pleasure working with such friendly and supportive people. A big thank you to Prof. Agarwal and the entire COSMOS team for everything!
In this edition of Cosmographer Corner, we highlight the work of former University of Arkansas at Little Rock graduate and cosmographer Dr. Maryam Maleki. We are extremely proud of Dr. Maleki’s accomplishments!
Dr. Maleki—who is now an assistant professor at California State University-Dominguez Hills teaching systems engineering and data analytics—started her graduate education at UA Little Rock in 2018, studying for a PhD in systems engineering. In her second year, Dr. Maleki joined COSMOS, and then went on to receive her PhD in 2022. We interviewed Dr. Maleki on where her career is now and what her work at COSMOS entailed, with her responses below.
How did COSMOS fit into your university career? How did you come across COSMOS and what were you studying when you joined COSMOS?
During my first year as a Ph.D. student, I worked with a different professor. However, in my second year, I discovered Dr. Agarwal’s work and became involved with COSMOS, which aligned with my research interests. COSMOS played a significant role in shaping my academic journey and became an integral part of my university experience. Although I began a new line of research when I joined COSMOS during my Ph.D. program, I was able to successfully graduate in July 2022, thanks to the incredible support of Dr. Agarwal and his amazing team.
My Ph.D. in Systems Engineering provided me with a strong foundation in mathematical modeling and statistical analysis. I integrated this expertise with information systems, particularly in the area of social media analysis. Through my work with COSMOS, I developed epidemiological models grounded in mathematical frameworks and applied them to social media research. My background in systems engineering complemented the data science research at COSMOS, enabling me to approach social media analysis from a unique and interdisciplinary perspective.
After earning my Ph.D., I pursued my goal of becoming a professor. I applied to various universities and received multiple job offers, ultimately choosing to accept the position of Visiting Assistant Professor in the Business Department at California State University, Fresno, where I worked for one year. This role was a pivotal step in advancing my academic career, which I am now continuing in a tenure-track position at my current university.
How did COSMOS contribute to your career and program at UALR? What was Dr. Agarwal’s role in your journeys during and after?
When I began working with COSMOS and Dr. Agarwal, I had no background in information systems. However, from the start, Dr. Agarwal and his team were incredibly welcoming and supportive, ensuring I never felt isolated. Each team member helped me in unique ways, offering guidance and encouragement. I vividly remember when my first paper was rejected. Dr. Agarwal reassured me, emphasizing that it was not a significant issue and encouraging me to learn from the experience to improve my research and publishing skills. His words of encouragement, coupled with his mentorship, helped me build self-confidence and provided valuable insights into the research process and how to make progress. This unwavering support played a crucial role in my development as a researcher during my time as his student.
Dr. Agarwal’s support has continued even after my graduation. I have had the opportunity to reconnect with him at various conferences, such as AMCIS and HICSS, and I also recently visited the new COSMOS offices in Little Rock. Dr. Agarwal consistently offers valuable guidance on how I can advance in my career, achieve greater success, apply for grants, and submit proposals. His mentorship, along with his generosity in sharing his time and expertise, is deeply appreciated, as such support is not always readily available.
I am honored to continue collaborating on ongoing research with Dr. Agarwal and his exceptional team. Being part of COSMOS has been a privilege, and I am truly grateful for the experience.
How would you describe the “research pipeline” that you worked on while at COSMOS? In other words, what was the specific area in which you researched?
My background in mathematical modeling enabled me to apply epidemiological models—typically used to study the spread of viruses—to analyze the dissemination of various types of information, such as misinformation, opposing viewpoints, and toxicity. By leveraging mathematical models based on differential equations, I explored whether information like misinformation or toxic content could spread in a ‘contagious’ manner, similar to the spread of a virus. During my studies, COVID-19 was a prominent topic, and much of my research focused on misinformation and toxic content related to the pandemic. My HICSS 2023 paper was, if I’m not mistaken, one of the first to apply epidemiological modeling to the analysis of toxic content.
Since leaving COSMOS, what positions have you had? What is your current work? What positions did COSMOS and your classes at UALR best prepare you for?
I began my university teaching career as a Visiting Assistant Professor in the Business Department at California State University, Fresno, where I taught for one year. I am currently a tenure-track faculty member at California State University, Dominguez Hills, teaching various courses in the Systems Engineering program. Some of my courses focus on data analytics, drawing on my expertise in Python, coding, and machine learning—skills I developed during my Ph.D. program. Additionally, I teach foundational physics courses
.
When I first joined COSMOS, I was new to the field and started from scratch, teaching myself essential skills for my research, including Python and machine learning. One key source of support was the mentorship I received from COSMOS postdocs, particularly Dr. Mead, whose mentoring approach has had a lasting impact on my own. Additionally, Dr. Wale played a crucial role in helping me identify my research interests during my time at COSMOS.
The mentorship and support I received during my Ph.D. program, especially when I needed it most, inspired me and taught me how to be an effective mentor for students new to the research world. I now apply these lessons to guide my students, many of whom are just beginning to learn how to conduct research. I currently lead a research team of seven students as research assistants, and the guidance I received has profoundly shaped my approach to mentoring others.
If you had to describe the most momentous event at COSMOS, what would it be?
During my time as a Ph.D. student in COSMOS, much of my research took place during the COVID-19 pandemic, which required us to work remotely for the majority of those years. As a result, I was unable to attend in-person conferences and had to present my papers virtually. Additionally, there were fewer events compared to what is available today.
Despite these challenges, we had the opportunity to be interviewed by local media outlets. In May 2020, we were featured on KARK, the NBC affiliate in Little Rock, where we discussed our research on the spread of COVID-19 misinformation. In May 2021, we were again interviewed by THV11, a Little Rock news station, to further explore our work on COVID-19 misinformation. These experiences were incredibly motivating and reinforced the significance of the research we were conducting.
What advice would you have for current Cosmographers?
I advise students to focus on developing both hard and soft skills simultaneously. While hard skills—such as coding, learning various tools and techniques, conducting research, and acquiring technical expertise—are essential for success, soft skills are equally important. Building a problem-solving mindset, teamwork abilities, time management, and effective communication are critical for professional growth. Professionalism and the ability to collaborate effectively are vital in any work environment.
Working in COSMOS, a team of experienced professionals, provides an excellent opportunity to practice and refine both skill sets. Although soft skills can be more challenging to assess and develop, they are fundamental in academic and career success. COSMOS offers a supportive environment where you can cultivate these essential skills, preparing you for a successful future.
